Abstract
Background: In this study, we used the total amount of insurance claims from patients in Nigeria as the data to investigate the direct and indirect effects of the diagnoses. Methods: We applied the Directed Acyclic Graph (DAG) with the total amount of the claims for each month for 89 diagnoses using datasets drawn from private insurance companies in Nigeria from January 2015 to September 2016, which provided 21 records for each diagnosis. Results: The result from DAG showed three pairs of direct effects: (1) Absolute Neutrophil Count (ANC) had a direct effect on appendectomy, (2) Sexually Transmitted Infections (STIs) had a direct effect on caesarean section, and (3) Glaucoma had a direct effect on insomnia. Conclusion: The most interesting result pertained to the third pair of diagnoses which is pertinent to research worldwide. We not only explored the relationship in a scientific way, but also the direction of the effect provided a basis for recommendations for healthcare in Nigeria and worldwide.
Highlights
IntroductionThe Directed Acyclic Graph (DAG) was used for the first time to analyze health insurance data
In the present study, the Directed Acyclic Graph (DAG) was used for the first time to analyze health insurance data
We focused on exploring the relationship between diagnoses based on insurance data in a scientific way
Summary
The Directed Acyclic Graph (DAG) was used for the first time to analyze health insurance data. Established techniques that had been used to analyze insurance data included neural networks [2 - 6], decision tree [7, 8], association rules [9], Bayesian network [10], and genetic algorithms [11, 12]. These techniques were used primarily for detecting fraud, not for investigations related to. In our application of DAG to health insurance data, the most interesting result in terms of the 89 diagnoses is that glaucoma has a direct effect on insomnia. We used the total amount of insurance claims from patients in Nigeria as the data to investigate the direct and indirect effects of the diagnoses
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